Investor Behavior & Fair Value

{ Euclidean Q3 2016 Letter }

While Euclidean’s YTD results and the monthly numbers behind them seem somewhat “placid”, they mask wide intra-month and daily swings. As investors have focused on macro developments (e.g., Brexit, speculation around potential Fed action, the election, etc.), our companies’ share prices have made big moves even when there has been no company-related news or new financial results.

These recent swings have occurred in the context of a long-lived bull market. During recent years, the most expensive stocks attracted a dominant share of investment dollars and upward price momentum, while the most undervalued stocks lagged behind. As a result, the valuation difference between the two groups widened. Certainly, if interest rates remain low and investor enthusiasm for fast-growing companies strengthens, this spread may remain or widen further.

However, as occurred with other market cycles, it feels as if investor attention is returning to the here-and-now of what they own. Although investor actions often push companies’ values far above and below what their current fundamentals suggest might be fair value, history shows us that companies’ earnings serve as a long-term attractor to their market prices. [1]

Thus, what ultimately carries the day when investing is the relationship between a company’s business strength and its market price. Both parts matter. The fastest-growing businesses have often proven to be terrible investments when bought at very high prices. And, companies experiencing recent setbacks have often turned into big winners when bought at points of high pessimism.

Our point of view has been informed by using machine learning to seek lessons for investing in public companies that could put odds on our side across a market cycle. The lessons we found have us avoiding investments in companies whose market values cannot be justified on the basis of previous, actual results. Instead, we direct Euclidean’s investment dollars toward companies with good qualities and long operating histories when their shares are offered at pessimistic prices. In this sense, we are deep-value investors.

The output of our process is a current portfolio consisting of established companies that are collectively offered at a 50%+ discount to market multiples even as they demonstrate strength in other fundamental areas. Aside from the general advantage that buying inexpensive stocks has demonstrated in the past, our optimism about maintaining this positioning in this environment derives from the following observations:

In previous market cycles, expensive “growth” stocks have come in and out of fashion in relation to their inexpensive “value” counterparts. There is some evidence [2] that we are emerging from the longest period in recent history of growth outperforming value. When this has occurred in the past, value strategies have historically gone on to deliver strong absolute and relative returns.

The market as a whole is expensive in relation to earnings. It is reasonable to expect valuation multiples to compress over time. While value investing has delivered attractive results across previous market cycles, its performance advantage appears to have been most pronounced across years of compressing earnings multiples.

Thus, given this environment, our process, and the portfolio we hold, we are optimistic about Euclidean’s prospects. Although we cannot control how the markets value our holdings in the short term, we do control where we devote our energy along the way. Our primary focus is adhering to an investment process that we believe is well positioned to capitalize on the opportunity just described.

While we do so and oversee the fund, we also live in an interesting time — there is a great renaissance going on with the technologies that we use to find meaning in the vast body of corporate and stock market history. These tools are behind improvements in self-driving cars, computers that can teach themselves how to master various games, and machines that have achieved better-than-human skill at image recognition. So, we devote the balance of our energy to exploring how the technologies and practices behind these developments might add to our investment process in the future.

To help you understand the work that we do and empower you to better evaluate our thinking, we have recently begun to describe a recent research project through a series of blog posts that comprise the Deep Learning & Long-Term Investing Blog Series. If you are interested in how to structure the data and use algorithms to predict how a stock will perform, then you might enjoy reading these posts. Or, if you would like to understand some of the big challenges inherent in model building and how to address them, then pour yourself a cup of coffee and read away.

In the meantime, please reflect on this parting view: while it’s easy to make predictions, it’s not so easy to make predictions that come true. The forecasts of market “gurus” are accurate less than half the time [3], and analysts show a strong tendency to predict that recent trends will continue into the future [4]. Even company CFOs show an astonishing inability to predict where the market will be 12 months from now [5].

Thus, devoting energy to predicting macroeconomic and political developments, or attempting to time the market, seems like a fool’s errand. In our view, what matters most is having a sound investment process and adhering to it across a very long period of time.

The opinions expressed herein are those of Euclidean Technologies Management, LLC (“Euclidean”) and are subject to change without notice. This material is not financial advice or an offer to purchase or sell any product. Euclidean reserves the right to modify its current investment strategies and techniques based on changing market dynamics or client needs.

Euclidean Technologies Management, LLC is an independent investment adviser registered under the Investment Advisers Act of 1940, as amended. Registration does not imply a certain level of skill or training. More information about Euclidean including our investment strategies, fees and objectives can be found in our ADV Part 2, which is available upon request.

[4] To explore some of the data regarding the futility of forecasting, please see the following resources: David Dreman – Contrarian Investment Strategies; James Montier – The Seven Sins of Fund Management; Phillip Tetlock – Expert Political Judgment How Good Is It? How Can We Know?

We share these numbers because they are easy-to-communicate measures that show the results of our systematic process for buying shares in historically sound companies when their earnings are on sale. [6] [7]

It is important to note that Euclidean uses similar concepts but different measures to assess individual companies as potential investments. Our models look at certain metrics over longer periods and seek to understand their volatility and rate of growth. Our process also makes a series of adjustments to company financial statements that our research has found to more accurately assess results, makes complex trade-offs between measures, and so on. These numbers should, however, give you a sense of what you own as a Euclidean Investor. In general, higher numbers for these measures are more attractive. The key measures are:

Earnings Yield – This measures how inexpensive a company is in relation to its demonstrated ability to generate cash for its owners. A company with twice the earnings yield as another is half as expensive; therefore, all else being equal, we seek companies with very high Earnings Yields. Earnings Yield reflects a company’s past four-year average earnings before interest and tax, divided by its current enterprise value (enterprise value = market value + debt – cash).

Return on Capital – This measures how well a company has historically generated cash for its owners in relation to how much capital has been invested (equity and long-term debt) in the business. At its highest level, this measure reflects two important things. First, it is an indicator of whether a company’s business is efficient at deploying capital in a way that generates additional income for its shareholders. Second, it indicates whether management has good discipline in deciding what to do with the cash it generates. For example, all else being equal, companies that overpay for acquisitions, or retain more capital than they can productively deploy, will show lower returns on capital than businesses that do the opposite. Return on Capital reflects a company’s four-year average earnings before interest and tax, divided by its current equity + long-term debt.

Equity / Assets – This measures how much of a company’s assets can be claimed by its common shareholders versus being claimed by others. High numbers here imply that the company owns a large portion of its figurative “house” and, all else being equal, indicates a better readiness to weather tough times.

Revenue Growth Rate – This is the annualized rate a company has grown over the past four years.

[6] All Euclidean measures are formed by summing the values of Euclidean’s pro-rata share of each portfolio company’s financials. That is, if Euclidean owns 1% of a company’s shares, it first calculates 1% of that company’s market value, revenue, debt, assets, earnings, and so on. Then, it sums those numbers with its pro-rata share of all other portfolio companies. This provides the total revenue, assets, earnings, etc. across the portfolio that are used to calculate the portfolio’s aggregate measures presented here.

[7] The S&P 500 measures are calculated in a similar way as described above. The market values, revenue, debt, assets, earnings, etc., for each company in the S&P 500 are added together. Those aggregate numbers are then used to calculate the metrics above. For example, the earnings yield of the S&P 500 is calculated as the total average four-year earnings before interest and taxes across all 500 companies divided by those companies’ collective enterprise values (all 500 companies’ market values + cash – debt).

Euclidean’s Ten Largest Holdings as of SEPTEMBER 30, 2016

We provide this information because many of you have expressed an interest in talking through individual positions as a means of better understanding how our investment process seeks value.

We are available to discuss these holdings with you at your convenience. We are happy to explain both why our models have found these companies to be attractive as well as our sense of why the market has been pessimistic about their future prospects.

Euclidean’s ten largest positions as of September 30, 2016 (in alphabetical order) [8]

ACCO Brands – ACCO

Anixter International – AXE

Best Buy – BBY

Capella Education – CPLA

CRA International – CRAI

Deckers Outdoor – DECK

DeVry Education Group – DV

Iconix Brand Group – ICON

Lear Corporation – LEA

Western Digital – WDC

[8] There is no assurance that any securities discussed herein will remain in the Fund at the time you receive this report or that securities sold have not been repurchased. It should not be assumed that any of the securities transactions, holdings or sectors discussed were or will be profitable, or that the investment recommendations or decisions Euclidean makes in the future will be profitable or equal the performance of the securities discussed herein. There is no assurance that any securities, sectors or industries discussed herein will be included in or excluded from the Fund’s holdings.

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